Abstract: In this study, it is predicted by density functional theory calculations that graphene-like novel ultra-thin phases of manganese fluoride crystals, that have nonlayered structures in their bulk form, can be stabilized by fluorination of manganese dichalcogenide crystals. First, it is shown that substitution of fluorine atoms with chalcogens in the manganese dichalcogenide host lattice is favorable. Among possible crystal formations, three stable ultra-thin structures of manganese fluoride, 1H-MnF2, 1T-MnF2 and MnF3, are found to be stable by total energy optimization calculations. In addition, phonon calculations and Raman activity analysis reveal that predicted novel single-layers are dynamically stable crystal structures displaying distinctive characteristic peaks in their vibrational spectrum enabling experimental determination of the corresponding phases. Differing from 1H-MnF2 antiferromagnetic (AFM) large gap semiconductor, 1T-MnF2 and MnF3 single-layers are semiconductors with ferromagnetic (FM) ground state.

Abstract: Vibrational thermal properties of CuZn2InTe4, AgZn2InTe4, and Cu2CdSnTe4, derived from binary II-VI zinc-blendes, are reported based on first-principles calculations. While the chalcogenide atoms in these materials have the same lattice positions, the cation atom arrangements vary, resulting in different crystal symmetries and subsequent properties. The compositional differences have important effects on the vibrational thermal characteristics of the studied materials, which demonstrate that low-frequency optical phonons hybridize with acoustic phonons and lead to enhanced phonon-phonon scattering and low lattice thermal conductivities. The phonon density of states, mode Gruneisen parameters, and phonon scattering rates are also calculated, enabling deeper insight into the microscopic thermal conduction processes in these materials. Compositional variations drive differences among the three materials considered here; nonetheless, their structural similarities and generally low thermal conductivities (0.5-4 W/mK at room temperature) suggest that other similar II-VI zinc-blende derived materials will also exhibit similarly low values, as also corroborated by experimental data. This, combined with the versatility in designing a variety of motifs on the overall structure, makes quaternary chalcogenides interesting for thermal management and energy conversion applications that require low thermal conductivity.

Abstract: The Stark effect is one of the most efficient mechanisms to manipulate many-body states in nanostructured systems. In mono- and few-layer transition metal dichalcogenides, it has been successfully induced by optical and electric field means. Here, we tune the optical emission energies and dissociate excitonic states in MoSe2 monolayers employing the 220 MHz in-plane piezoelectric field carried by surface acoustic waves. We transfer the monolayers to high dielectric constant piezoelectric substrates, where the neutral exciton binding energy is reduced, allowing us to efficiently quench (above 90%) and red-shift the excitonic optical emissions. A model for the acoustically induced Stark effect yields neutral exciton and trion in-plane polarizabilities of 530 and 630 x 10(-5) meV/(kV/cm)(2), respectively, which are considerably larger than those reported for monolayers encapsulated in hexagonal boron nitride. Large in-plane polarizabilities are an attractive ingredient to manipulate and modulate multiexciton interactions in two-dimensional semiconductor nanostructures for optoelectronic applications.

Abstract: Direct experimental measurement of thermal expansion coefficient without substrate effects is a challenging task for two-dimensional (2D) materials, and its accurate estimation with large-scale ab initio molecular dynamics is computationally very expensive. Machine learning-based interatomic potentials trained with ab initio data have been successfully used in molecular dynamics simulations to decrease the computational cost without compromising the accuracy. In this study, we investigated using Gaussian approximation potentials to reproduce the density functional theory-level accuracy for graphene within both lattice dynamical and molecular dynamical methods, and to extend their applicability to larger length and time scales. Two such potentials are considered, GAP17 and GAP20. GAP17, which was trained with pristine graphene structures, is found to give closer results to density functional theory calculations at different scales. Further vibrational and structural analyses verify that the same conclusions can be deduced with density functional theory level in terms of the reasoning of the thermal expansion behavior, and the negative thermal expansion behavior is associated with long-range out-of-plane phonon vibrations. Thus, it is argued that the enabled larger system sizes by machine learning potentials may even enhance the accuracy compared to small-size-limited ab initio molecular dynamics.

Abstract: The rational design of two-dimensional (2D) piezoelectric materials has recently garnered great interest due to their increasing use in technological applications, including sensor technology, actuating devices, energy harvesting, and medical applications. Several materials possessing high piezoelectric response have been reported so far, but a high-throughput first-principles approach to estimate the piezoelectric potential of layered materials has not been performed yet. In this study, we systematically investigated the piezoelectric (e(11), d(11)) and elastic (C-11 and C-12) properties of 128 thermodynamically stable 2D semiconductor materials by employing first-principle methods. Our high-throughput approach demonstrates that the materials containing Group-V elements produce significantly high piezoelectric strain constants, d(11) > 40 pm V-1, and 49 of the materials considered have the e(11) coefficient higher than MoS2 insomuch as BrSSb has one of the largest d(11) with a value of 373.0 pm V-1. Moreover, we established a simple empirical model in order to estimate the d(11) coefficients by utilizing the relative ionic motion in the unit cell and the polarizability of the individual elements in the compounds.

Abstract: We present here a new interatomic potential parameter set to predict the thermal conductivity of zirconium trisulfide monolayers. The generated Tersoff-type force field is parameterized using data collected with first-principles calculations. We use non-equilibrium molecular dynamics simulations to predict the thermal conductivity. The generated parameters result in very good agreement in structural, mechanical, and dynamical parameters. The room temperature lattice thermal conductivity ( kappa) of the considered crystal is predicted to be kappa x x = 25.69Wm – 1K – 1 and kappa y y = 42.38Wm – 1K – 1, which both agree well with their corresponding first-principles values with a discrepancy of less than 5%. Moreover, the calculated kappa variation with temperature (200 and 400 K) are comparable within the framework of the accuracy of both first-principles and molecular dynamics simulations.

Abstract: The structure and thermal boundary conductance of the wurtzite GaN/AlN (0001) interface are investigated using molecular dynamics simulation. Simulation results with three different empirical interatomic potentials have produced similar misfit dislocation networks and dislocation core structures. Specifically, the misfit dislocation network at the GaN/AlN interface is found to consist of pure edge dislocations with a Burgers vector of 1/3(1 (2) over bar 10) and the misfit dislocation core has an eight-atom ring structure. Although different interatomic potentials lead to different dislocation properties and thermal conductance values, all have demonstrated a significant effect of misfit dislocations on the thermal boundary conductance of the GaN/AlN (0001) interface. Published under an exclusive license by AIP Publishing.

Abstract: The theoretical investigation on structural, vibrational, and electronic properties of zinc-blende (ZB) AgI were carried out employing first principles density functional theory calculations. Thermoelectric properties then were predicted through semi-classical Boltzmann transport equations within the constant relaxation time approximation. Equilibrium lattice parameter, bulk modulus, elastic constants, and vibrational properties were calculated by using generalized gradient approximation. Calculated properties are in good agreement with available experimental values. Electronic and thermoelectric properties were investigated both with and without considering spin-orbit coupling (SOC) effect which is found to have a strong influence on p-type Seebeck coefficient as well as the power factor of the ZB-AgI. By inclusion of SOC, a reduction of the band-gap and p-type Seebeck coefficients as well as the power factor was found which is the indication of that spin-orbit interaction cannot be ignored for p-type thermoelectric properties of the ZB-AgI. By using deformation potential theory for electronic relaxation time and experimentally predicted lattice thermal conductivity, we obtained aZTvalue 1.69 (0.89) at 400 K for n-type (p-type) carrier concentration of 1.5 x 10(18)(4.6 x10(19)) cm(-3)that makes ZB-AgI as a promising room temperature thermoelectric material.

Abstract: Using first-principles calculations we systematically investigate the atomic, electronic and magnetic properties of novel two-dimensional materials (2DM) with a stoichiometry C3N which has recently been synthesized. We investigate how the number of layers affect the electronic properties by considering monolayer, bilayer and trilayer structures, with different stacking of the layers. We find that a transition from semiconducting to metallic character occurs which could offer potential applications in future nanoelectronic devices. We also study the affect of width of C3N nanoribbons, as well as the radius and length of C3N nanotubes, on the atomic, electronic and magnetic properties. Our results show that these properties can be modified depending on these dimensions, and depend markedly on the nature of the edge states. Functionalization of the nanostructures by the adsorption of H adatoms is found induce metallic, half-metallic, semiconducting and ferromagnetic behavior, which offers an approach to tailor the properties, as can the application of strain. Our calculations give insight into this new family of C3N nanostructures, which reveal unusual electronic and magnetic properties, and may have great potential in applications such as sensors, electronics and optoelectronic at the nanoscale.

Abstract: Novel stable ultra-thin phases of europium oxide are investigated by means of state-of-the-art first principles calculations. Total energy calculations show that single layers of EuO2 and Eu(OH)(2) can be stabilized in an octahedrally coordinated (1T) atomic structure. However, phonon calculations reveal that although both structures are energetically feasible, only the 1T-EuO2 phase has dynamical stability. The phonon spectrum of 1T-EuO2 displays three Raman active modes; a non-degenerate out-of-plane A(1g) mode at 353.5 cm(-1) and two doubly-degenerate in-plane E-g modes at 304.3 cm(-1). Furthermore, magnetic ground state and electronic band dispersion calculations show that the single layer EuO2 is a metal with net magnetic moment of 5(mu B) per unitcell resulting in a half-metallic ferrimagnetic behavior. Moreover, robustness of the half-metallic ferrimagnetic characteristics of EuO2 is confirmed by the application of electric field and charging. Single layer 1T-EuO2, with its stable ultra-thin structure and half-metallic ferrimagnetic feature, is a promising novel material for nanoscale electronic and spintronic applications.

Abstract: The pyroantimonate pigments Naples yellow and lead tin antimonate yellow are recognized as some of the most stable synthetic yellow pigments in the history of art. However, this exceptional lightfastness is in contrast with experimental evidence suggesting that this class of mixed oxides is of semiconducting nature. In this study the electronic structure and light-induced behavior of the lead pyroantimonate pigments were determined by means of a combined multifaceted analytical and computational approach (photoelectrochemical measurements, UV-vis diffuse reflectance spectroscopy, STEM-EDS, STEM-HAADF, and density functional theory calculations). The results demonstrate both the semiconducting nature and the lightfastness of these pigments. Poor optical absorption and minority carrier mobility are the main properties responsible for the observed stability. In addition, novel fundamental insights into the role played by Na atoms in the stabilization of the otherwise intrinsically unstable Pb2Sb2O7 pyrochlore were obtained.

Abstract: Recent years have seen a tremendous rise of two-dimensional (2D) magnetic materials, several of which were verified experimentally. However, most of the theoretical predictions to date rely on ab initio methods, at zero temperature and fluctuation-free, while one certainly expects detrimental quantum fluctuations at finite temperatures. Here, we present the solution of the quantum Heisenberg model for honeycomb/hexagonal lattices with anisotropic exchange interaction up to third nearest neighbors and in an applied field in arbitrary direction, which answers the question whether long-range magnetization can indeed survive in the ultrathin limit of materials, up to which temperature, and what the characteristic excitation (magnon) frequencies are, all essential to envisaged applications of magnetic 2D materials. We find that long-range magnetic order persists at finite temperature for materials with overall easy-axis anisotropy. We validate the calculations on the examples of monolayers CrI3, CrBr3, and MnSe2. Moreover, we provide an easy-to-use tool to calculate Curie temperatures of new 2D computational materials.

Abstract: The surface termination of MXenes greatly determines the electrochemical properties and ion kinetics on their surfaces. So far, hydroxyl-, oxygen-, and fluorine-terminated MXenes have been widely studied for energy storage applications. Recently, sulfur-functionalized MXene structures, which possess low diffusion barriers, have been proposed as candidate materials to enhance battery performance. We performed first-principles calculations on the structural, stability, electrochemical, and ion dynamic properties of Li-adsorbed sulfur-functionalized groups 3B, 4B, 5B, and 6B transition-metal (M)-based MXenes (i.e., M2CS2 with M = Sc, Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, and W). We performed phonon calculations, which indicated that all of the above M2CS2 MXenes, except for Sc, are dynamically stable at T = 0 K. The ground-state structure of each M2CS2 monolayer depends on the type of M atom. For instance, while sulfur prefers to sit at the FCC site on Ti2CS2, it occupies the HCP site of Cr-based MXene. We determined the Li adsorption configurations at different concentrations using the cluster expansion method. The highest maximum open-circuit voltages were computed for the group 4B element (i.e., Ti, Zr, and Hf)-based M2CS2, which are larger than 2.1 V, while their average voltages are approximately 1 V. The maximum voltage for the group 6B element (i.e., Cr, Mo, W)-based M2CS2 is less than 1 V, and the average voltage is less than 0.71 V. We found that S functionalization is helpful for capacity improvements over the O-terminated MXenes. In this respect, the computed storage gravimetric capacity may reach up to 417.4 mAh/g for Ti2CS2 and 404.5 mAh/g for V2CS2. Ta-, Cr-, Mo-, and W-based M2CS2 MXenes show very low capacities, which are less than 100 mAh/g. The Li surface diffusion energy barriers for all of the considered MXenes are less than 0.22 eV, which is favorable for high charging and discharging rates. Finally, ab initio molecular dynamic simulations performed at 400 K and bond-length analysis with respect to Li concentration verify that selected promising systems are robust against thermally induced perturbations that may induce structural transformations or distortions and undesirable Li release.

Abstract: We analyze the phenomenon of back hopping in spin-torque induced switching of the magnetization in perpendicularly magnetized tunnel junctions. The analysis is based on single-shot time-resolved conductance measurements of the pulse-induced back hopping. Studying several material variants reveals that the back hopping is a feature of the nominally fixed system of the tunnel junction. The back hopping is found to proceed by two sequential switching events that lead to a final state P' of conductance close to-but distinct from-that of the conventional parallel state. The P' state does not exist at remanence. It generally relaxes to the conventional antiparallel state if the current is removed. The P' state involves a switching of the sole spin-polarizing part of the fixed layers. The analysis of literature indicates that back hopping occurs only when the spin-polarizing layer is too weakly coupled to the rest of the fixed system, which justifies a posteriori the mitigation strategies of back hopping that were implemented empirically in spin-transfer-torque magnetic random access memories.

Abstract: The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionalities is that, after they have learned a probability distribution from a dataset, they allow exact and efficient sampling of typical system configurations. Here we employ a neural autoregressive distribution estimator (NADE) to boost Markov chain Monte Carlo (MCMC) simulations of a paradigmatic classical model of spin-glass theory, namely, the two-dimensional Edwards-Anderson Hamiltonian. We show that a NADE can be trained to accurately mimic the Boltzmann distribution using unsupervised learning from system configurations generated using standard MCMC algorithms. The trained NADE is then employed as smart proposal distribution for the Metropolis-Hastings algorithm. This allows us to perform efficient MCMC simulations, which provide unbiased results even if the expectation value corresponding to the probability distribution learned by the NADE is not exact. Notably, we implement a sequential tempering procedure, whereby a NADE trained at a higher temperature is iteratively employed as proposal distribution in a MCMC simulation run at a slightly lower temperature. This allows one to efficiently simulate the spin-glass model even in the low-temperature regime, avoiding the divergent correlation times that plague MCMC simulations driven by local-update algorithms. Furthermore, we show that the NADE-driven simulations quickly sample ground-state configurations, paving the way to their future utilization to tackle binary optimization problems.